LogParabola¶

class sherpa.models.basic.LogParabola(name='logparabola')[source] [edit on github]¶

Bases: sherpa.models.model.RegriddableModel1D

One-dimensional log-parabolic function.

ref¶: The reference point for the normalization.

c1¶: The power-law index (gamma).

c2¶: The curvature of the parabola (beta).

ampl¶: The amplitude of the model.

See also

Exp, Exp10, Log, Log10, Sqrt

Notes

The functional form of the model for points is:

f(x) = ampl * (x / ref) ^ (-c1 - c2 * log_10 (x / ref))

The grid version is evaluated by numerically intgerating the function over each bin using a non-adaptive Gauss-Kronrod scheme suited for smooth functions 1, falling over to a simple trapezoid scheme if this fails.

References

1: https://www.gnu.org/software/gsl/manual/html_node/QNG-non_002dadaptive-Gauss_002dKronrod-integration.html

Attributes Summary

`ndim`
`thawedparhardmaxes`	The hard maximum values for the thawed parameters.
`thawedparhardmins`	The hard minimum values for the thawed parameters.
`thawedparmaxes`	Access to the maximum limits for the thawed parameters
`thawedparmins`	Access to the minimum limits for the thawed parameters
`thawedpars`	Access to the thawed parameters of the model

Methods Summary

`apply`(outer, otherargs, *otherkwargs)
`calc`(pars, xlo, args, *kwargs)	Evaluate the model on a grid.
`get_center`()
`guess`(dep, args, *kwargs)	Set an initial guess for the parameter values.
`regrid`(args, *kwargs)	The class RegriddableModel1D allows the user to evaluate in the requested space then interpolate onto the data space.
`reset`()	Reset the parameter values.
`set_center`(args, *kwargs)
`startup`([cache])	Called before a model may be evaluated multiple times.
`teardown`()	Called after a model may be evaluated multiple times.

Attributes Documentation

ndim = 1¶

thawedparhardmaxes¶: The hard maximum values for the thawed parameters.

thawedparhardmins¶: The hard minimum values for the thawed parameters.

thawedparmaxes¶: Access to the maximum limits for the thawed parameters

thawedparmins¶: Access to the minimum limits for the thawed parameters

thawedpars¶: Access to the thawed parameters of the model

Methods Documentation

apply(outer, *otherargs, **otherkwargs) [edit on github]¶

calc(pars, xlo, *args, **kwargs) [edit on github]¶

Evaluate the model on a grid.

Parameters

p (sequence of numbers) – The parameter values to use. The order matches the pars field.
*args – The model grid. The values can be scalar or arrays, and the number depends on the dimensionality of the model and whether it is being evaluated over an integrated grid or at a point (or points).

get_center() [edit on github]¶

guess(dep, *args, **kwargs) [edit on github]¶

Set an initial guess for the parameter values.

Attempt to set the parameter values, and ranges, for the model to match the data values. This is intended as a rough guess, so it is expected that the model is only evaluated a small number of times, if at all.

regrid(*args, **kwargs) [edit on github]¶

The class RegriddableModel1D allows the user to evaluate in the requested space then interpolate onto the data space. An optional argument ‘interp’ enables the user to change the interpolation method.

Examples

>>> import numpy as np
>>> from sherpa.models.basic import Box1D
>>> mybox = Box1D()
>>> request_space = np.arange(1, 10, 0.1)
>>> regrid_model = mybox.regrid(request_space, interp=linear_interp)

reset() [edit on github]¶: Reset the parameter values.

set_center(*args, **kwargs) [edit on github]¶

startup(cache=False) [edit on github]¶

Called before a model may be evaluated multiple times.

Parameters: cache (bool, optional) – Should a cache be used when evaluating the models.